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Group_cohesion_leader_follower.py
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# -*- coding: utf-8 -*-
"""
Created on Tue May 4 09:07:52 2021
@author: savan
"""
#Different sender:receiver initial concentration
#Formation of leader-follower relationship
from plate import Plate
from species import Species
import numpy as np
import helper_functions as hf
def main():
## experimental parameters
D = 0.03
rho_n = 0.5
rc = 3.33e-2 #6e-4
Dc = 1e-5
w = 0.75
Da = 2.94e-6
rho_A = 0.01
Dt = 0
environment_size = (59, 59)
concsS=[0.01,0.1,1,1,1]
concsR=[1,1,1,0.1,0.01]
for col in range(len(concsS)):
plate = Plate(environment_size)
##add nutrient to the plate
U_N = np.zeros(environment_size)
for i in np.linspace(0, 58, 59):
for j in np.linspace(0,58,59):
U_N[int(i),int(j)]=100
N = Species("N", U_N)
def N_behaviour(species, params):
## unpack params
D, rho_n, Dc, rc, w, rho_A, Da, Dt = params
n = D*hf.ficks(species['N'], w) - (species['R']+(species['S']))*rho_n*hf.leaky_hill(s=species['N'], K=80, lam=1, max=rc, min=0)
return n
N.set_behaviour(N_behaviour)
plate.add_species(N)
##add sender strain to the plate
U_S = np.zeros(environment_size)
for i in np.linspace(29, 29, 1):
U_S[int(i), int(i)] = 0.001*concsS[col]
S = Species("S", U_S)
def S_behaviour(species, params):
## unpack params
D, rho_n, Dc, rc, w, rho_A, Da, Dt = params
s = Dc * hf.ficks(species['S'], w)*hf.leaky_hill(s=species['T']+species['A'], K=40e-9, lam=2, max=2.75, min=1) + species['S']*hf.leaky_hill(s=species['N'], K=80, lam = 1, max=rc, min=0)
return s
S.set_behaviour(S_behaviour)
plate.add_species(S)
##add uninformed strain to the plate
U_R = np.zeros(environment_size)
for i in np.linspace(29, 29, 1):
for j in np.linspace(29,29, 1):
U_R[int(i), int(j)] = 0.001*concsR[col]
R = Species("R", U_R)
def R_behaviour(species, params):
## unpack params
D, rho_n, Dc, rc, w, rho_A, Da, Dt = params
r = Dc*hf.leaky_hill(s=species['A'], K=40e-9, lam=2, max=2.75, min=1)*hf.ficks(species['R'], w) + species['R']*hf.leaky_hill(s=species['N'], K=80, lam = 1, max=rc, min=0)
return r
R.set_behaviour(R_behaviour)
plate.add_species(R)
##add AHL to plate
U_A = np.zeros(environment_size)
A = Species("A", U_A)
def A_behaviour(species, params):
##unpack params
D, rho_n, Dc, rc, w, rho_A, Da, Dt = params
a = Da * hf.ficks(species['A'], w) + rho_A*species['S']
return a
A.set_behaviour(A_behaviour)
plate.add_species(A)
##add target to plate
U_T = np.zeros(environment_size)
for j in np.linspace(0,58, environment_size[0]):
for i in np.linspace(30, 58, 29):
U_T[int(i), int(j)] = ((int(i))-29)/2.9
T = Species("T", U_T)
def T_behaviour(species, params):
## unpack params
D, rho_n, Dc, rc, w, rho_A, Da, Dt = params
t = Dt*hf.ficks(species['T'], w)
return t
T.set_behaviour(T_behaviour)
plate.add_species(T)
##target need induce more motility than ahl? different k 2/3rd than ahl
params = (D, rho_n, Dc, rc, w, rho_A, Da, Dt)
sim = plate.run(t_final = 200*60,
dt = 1.,
params = params)
#plate.plot_simulation(sim, 10)
S = plate.get_all_species()
plate.plot_conc_target(sim, S, 10, col)
#plate.compare_species(sim, S, 10, col)
main()